Preprocess: a set D of points in R d Query: given a new point q, report a point pD with the smallest distance to q q p Motivation

The kth-nearest neighbor rule is arguably the simplest and most intuitively appealing nonparametric classification procedure. However, application of this method is inhibited by lack of knowledge about its properties, in particular, about the manner in which it is influenced by the value of k; and by the absence of techniques for empirical choice of k. In the present paper we detail the way in ...

Text categorization or classification is the automated assigning of text documents to pre-defined classes based on their contents. Many of classification algorithms usually assume that the training examples are evenly distributed among different classes. However, unbalanced data sets often appear in many practical applications. In order to deal with uneven text sets, we propose the neighbor-wei...

Agent-based modeling and simulation, based on the cellular automata paradigm, is an approach to modeling complex systems comprised of interacting autonomous agents. Open questions in agent-based simulation focus on scale-up issues encountered in simulating large numbers of agents. Specifically, how many agents can be included in a workable agent-based simulation? One of the basic tenets of agen...

We consider feature selection and weighting for nearest neighbor classifiers. Atechnical challenge in this scenario is how to cope with discrete update of nearestneighbors when the feature space metric is changed during the learning process.This issue, called the target neighbor change, was not properly addressed in theexisting feature weighting and metric learning literature. I...

With the proliferation of wireless communications and the rapid advances in technologies for tracking the positions of continuously moving objects, algorithms for efficiently answering queries about large numbers of moving objects increasingly are needed. One such query is the reverse nearest neighbor (RNN) query that returns the objects that have a query object as their closest object. While a...

This paper presents a new approach for solving binary quantification problems based on nearest neighbor (NN) algorithms. Our main objective is to study the behavior of these methods in the context of prevalence estimation. We seek for NN-based quantifiers able to provide competitive performance while balancing simplicity and effectiveness. We propose two simple weighting strategies, PWK and PWK...

We study the convergence rates of neighbor joining and several new phylogenetic reconstruction methods on families of trees of bounded diameter. Our study presents theoretically obtained convergence rates, as well as an empirical study based upon simulation of evolution on random birth-death trees. We find that the new phylogenetic methods offer an advantage over the neighbor joining method, ex...